Deductible Costs for Bundled Insurance Contracts

Dong, Yumo; Frees, Edward W.; Huang, Fei

doi:10.2139/ssrn.4020299

Cited by 1 publication

(3 citation statements)

References 15 publications

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“…(2016), Shi and Yang (2018), Dong et al . (2022) among others for previous uses of the LGPIF data in actuarial science. The LGPIF is administered by the Wisconsin Office of the Commissioner of Insurance, with its overarching purpose being to make property insurance available for local government units.…”

Section: Application To Data From Wisconsin Local Government Property...mentioning

confidence: 99%

“…We illustrate an application of multi-state customer churn analysis to commercial insurance data, using a data set publicly available from the Wisconsin Local Government Property Insurance Fund (LGPIF); see Frees et al (2016), Shi and Yang (2018), Dong et al (2022) among others for previous uses of the LGPIF data in actuarial science. The LGPIF is administered by the Wisconsin Office of the Commissioner of Insurance, with its overarching purpose being to make property insurance available for local government units.…”

Section: Application To Data From Wisconsin Local Government Property...mentioning

confidence: 99%

“…According to the direct premium written reported by Brian Briggs (2021), the commercial market represents 49% of the total direct premium written in the US property & casualty insurance industry. Commercial insurance contracts can include several coverages such as building, equipment, and auto coverage, and it is common for customers to have multiple contracts with the same company or (alternatively) have multiple coverages under a single bundled contract (Dong et al ., 2022). Additionally, customers add or drop coverages, or switch providers entirely, on a regular basis to meet their benefits and budgets.…”

Section: Introductionmentioning

confidence: 99%

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Multi-State Modelling of Customer Churn

Dong

Frees²,

Huang³

et al. 2022

ASTIN Bull.

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Customer churn, which insurance companies use to describe the non-renewal of existing customers, is a widespread and expensive problem in general insurance, particularly because contracts are usually short-term and are renewed periodically. Traditionally, customer churn analyses have employed models which utilise only a binary outcome (churn or not churn) in one period. However, real business relationships are multi-period, and policyholders may reside and transition between a wider range of states beyond that of the simply churn/not churn throughout this relationship. To better encapsulate the richness of policyholder behaviours through time, we propose multi-state customer churn analysis, which aims to model behaviour over a larger number of states (defined by different combinations of insurance coverage taken) and across multiple periods (thereby making use of readily available longitudinal data). Using multinomial logistic regression (MLR) with a second-order Markov assumption, we demonstrate how multi-state customer churn analysis offers deeper insights into how a policyholder’s transition history is associated with their decision making, whether that be to retain the current set of policies, churn, or add/drop a coverage. Applying this model to commercial insurance data from the Wisconsin Local Government Property Insurance Fund, we illustrate how transition probabilities between states are affected by differing sets of explanatory variables and that a multi-state analysis can potentially offer stronger predictive performance and more accurate calculations of customer lifetime value (say), compared to the traditional customer churn analysis techniques.

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Section: Application To Data From Wisconsin Local Government Property...mentioning

confidence: 99%